Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/squadcodercom/squadcoder/hebrew-chatbot-buildernpx skills add squadcodercom/squadcoder --skill hebrew-chatbot-buildergit clone --depth 1 https://github.com/squadcodercom/squadcoderWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00212 | $0.09620 |
| Opus 5 | $0.00106 | $0.04810 |
| Sonnet 5 | $0.00042 | $0.01924 |
| Haiku 4.5 | $0.00021 | $0.00962 |
Grade A, and why
hebrew-chatbot-builder scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.post(url, json=payload, headers=headers) How it starts
The opening of the file, as written. The whole thing — 989 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hebrew Chatbot Builder
Build production-ready conversational AI chatbots with native Hebrew support. This skill covers platform integrations (WhatsApp, Telegram, web), Hebrew language patterns, RTL UI components, and conversation flow design for Hebrew speakers.
Instructions
Follow this procedure when building a Hebrew chatbot:
- Identify the platform/channel. Confirm whether the bot runs on WhatsApp Business API, Telegram, an embedded web widget, or several at once. Each has a different scaffold and message model.
- Confirm formal or informal register. Ask the user whether the audience expects informal Hebrew ("דוגרי", recommended for most consumer bots) or formal Hebrew (government, banking, legal). This decision shapes every response string.
- Ask the gender-handling strategy. Decide between asking the user's gender early and remembering it, using gender-neutral phrasing throughout, or slash notation ("את/ה"). See the Gender-Aware Responses section.
- Scaffold via the relevant bundled script. Use
scripts/whatsapp-webhook-handler.pyfor WhatsApp orscripts/telegram-bot-scaffold.pyfor Telegram as the starting point, then adapt the Hebrew response templates and conversation flows. - Wire entity extraction. Add
extract_israeli_entities()(or an equivalent) so the bot recognizes Israeli phone numbers, NIS amounts, dates, and Teudat Zehut from free-text Hebrew input. - Verify RTL rendering. For web widgets, set
dir="rtl"on the outermost container and test on a real device. For WhatsApp and Telegram, verify Hebrew text and interactive buttons render correctly on both iOS and Android.
Examples
Example 1: WhatsApp order-status bot in Hebrew
User says: "Build a WhatsApp bot in Hebrew that lets customers check their order status."
Actions:
- Identify the channel: WhatsApp Business Cloud API.
- Confirm informal register (consumer audience) and gender-neutral phrasing for broad reach.
- Start from
scripts/whatsapp-webhook-handler.py, which already includes webhook verification, signature checks, and Hebrew response templates. - Wire an interactive button menu ("בדיקת הזמנה", "שאלות נפוצות", "דבר/י עם נציג") and a
waiting_order_numberstate that validates the order number and looks it up. - Submit a Hebrew
order_confirmation_hetemplate via Meta Business Suite for proactive outbound updates.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 989 lines · 212 tokens per session scan A d84ccab0a6ec
hebrew-chatbot-builder is a skill published in the GitHub repository squadcodercom/squadcoder (11 stars, last pushed 2mo ago), licensed MIT. It adds 212 tokens to every session and 9,620 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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